Persymmetric adaptive polarimetric detection of subspace range-spread targets in compound Gaussian sea clutter

This paper focuses on the adaptive detection of range and Doppler dual-spread targets in non-homogeneous and nonGaussian sea clutter.The sea clutter from two polarimetric channels is modeled as a compound-Gaussian model with different parameters,and the target is modeled as a subspace rangespread target model.The persymmetric structure is used to model the clutter covariance matrix,in order to reduce the reliance on secondary data of the designed detectors.Three adaptive polarimetric persymmetric detectors are designed based on the generalized likelihood ratio test(GLRT),Rao test,and Wald test.All the proposed detectors have constant falsealarm rate property with respect to the clutter texture,the speckle covariance matrix.Experimental results on simulated and measured data show that three adaptive detectors outperform the competitors in different clutter environments,and the proposed GLRT detector has the best detection performance under different parameters.

Kullback-Leibler Divergence Based ISAC Constellation and Beamforming Design in the Presence of Clutter

Integrated sensing and communication(ISAC)is regarded as a pivotal technology for 6G communication.In this paper,we employ Kullback-Leibler divergence(KLD)as the unified performance metric for ISAC systems and investigate constellation and beamforming design in the presence of clutters.In particular,the constellation design problem is solved via the successive convex approximation(SCA)technique,and the optimal beamforming in terms of sensing KLD is proven to be equivalent to maximizing the signal-to-interference-plus-noise ratio(SINR)of echo signals.Numerical results demonstrate the tradeoff between sensing and communication performance under different parameter setups.Additionally,the beampattern generated by the proposed algorithm achieves significant clutter suppression and higher SINR of echo signals compared with the conventional scheme.

A general evaluation system for optimal selection performance of radar clutter model

The optimal selection of radar clutter model is the premise of target detection,tracking,recognition,and cognitive waveform design in clutter background.Clutter characterization models are usually derived by mathematical simplification or empirical data fitting.However,the lack of standard model labels is a challenge in the optimal selection process.To solve this problem,a general three-level evaluation system for the model selection performance is proposed,including model selection accuracy index based on simulation data,fit goodness indexs based on the optimally selected model,and evaluation index based on the supporting performance to its third-party.The three-level evaluation system can more comprehensively and accurately describe the selection performance of the radar clutter model in different ways,and can be popularized and applied to the evaluation of other similar characterization model selection.

Wind turbine clutter mitigation using morphological component analysis with group sparsity

To address the problem that dynamic wind turbine clutter(WTC)significantly degrades the performance of weather radar,a WTC mitigation algorithm using morphological component analysis(MCA)with group sparsity is studied in this paper.The ground clutter is suppressed firstly to reduce the morphological compositions of radar echo.After that,the MCA algorithm is applied and the window used in the short-time Fourier transform(STFT)is optimized to lessen the spectrum leakage of WTC.Finally,the group sparsity structure of WTC in the STFT domain can be utilized to decrease the degrees of freedom in the solution,thus contributing to better estimation performance of weather signals.The effectiveness and feasibility of the proposed method are demonstrated by numerical simulations.

Inversion for atmosphere duct parameters using real radar sea clutter

This paper addresses the problem of estimating the lower atmospheric refractivity （M profile） under nonstandard propagation conditions frequently encountered in low altitude maritime radar applications. The vertical structure of the refractive environment is modeled using five parameters and the horizontal structure is modeled using five parameters. The refractivity model is implemented with and without a priori constraint on the duct strength as might be derived from soundings or numerical weather-prediction models. An electromagnetic propagation model maps the refractivity structure into a replica field. Replica fields are compared with the observed clutter using a squared-error objective function. A global search for the 10 environmental parameters is performed using genetic algorithms. The inversion algorithm is implemented on the basis of S-band radar sea-clutter data from Wallops Island, Virginia （SPANDAR）. Reference data are from range-dependent refractivity profiles obtained with a helicopter. The inversion is assessed （i） by comparing the propagation predicted from the radar-inferred refractivity profiles with that from the helicopter profiles, （ii） by comparing the refractivity parameters from the helicopter soundings with those estimated. This technique could provide near-real-time estimation of ducting effects.

Improved Multistage Wiener Filters in Nonhomogeneous Clutter Environments

A new method combining space-time preprocessing with multistage Wiener filters（STPMWF）is proposed to improve the performance of space-time adaptive processing（STAP）in nonhomogeneous clutter scenario.The new scheme only requires the data from the primary range bin,thus it can suppress discrete interferers efficiently,without calculating the inverse of covariance matrix.Comparing to the original MWF approach,the proposed scheme can be regarded as practical solutions for robust and effective STAP of nonhomogeneous radar data.The theoretical analysis shows that our STPMWF is simple in implementation and fast in convergence.The numeric results by using simulated data exhibit a good agreement with the proposed theory.

Novel polarimetric detector for target detection in heterogeneous clutter

A detection of static or slowly moving targets in the inhomogeneous clutter of polarimetric radar is researched and a new detector without exploiting the training set is developed, which has a good performance against the inhomogeneous clutter. The decision rule ensures the constant false alarm rate (CFAR) with respect to the disturbance covariance matrix. Numerical results show the robustness of the proposed method against the inhomogeneous clutter. © 2016 Beijing Institute of Aerospace Information.

The estimation of lower refractivity uncertainty from radar sea clutter using the Bayesian-MCMC method

The estimation of lower atmospheric refractivity from radar sea clutter（RFC） is a complicated nonlinear optimization problem.This paper deals with the RFC problem in a Bayesian framework.It uses the unbiased Markov Chain Monte Carlo（MCMC） sampling technique,which can provide accurate posterior probability distributions of the estimated refractivity parameters by using an electromagnetic split-step fast Fourier transform terrain parabolic equation propagation model within a Bayesian inversion framework.In contrast to the global optimization algorithm,the Bayesian-MCMC can obtain not only the approximate solutions,but also the probability distributions of the solutions,that is,uncertainty analyses of solutions.The Bayesian-MCMC algorithm is implemented on the simulation radar sea-clutter data and the real radar seaclutter data.Reference data are assumed to be simulation data and refractivity profiles are obtained using a helicopter.The inversion algorithm is assessed（i） by comparing the estimated refractivity profiles from the assumed simulation and the helicopter sounding data;（ii） the one-dimensional（1D） and two-dimensional（2D） posterior probability distribution of solutions.

Study on Dim Target Detection and Discrimination from Sea Clutter

Dim target detection from sea clutter is one of the difficult topics in ocean remote sensing application. By aiming at the shortcoming of false alarms when using track before detect （TBD） based on dynamic programming, a new discrimination method called statistics of direction histogram （SDH） is proposed, which is based on different features of trajectories between the true target and false one. Moreover, a new series of discrimination schemes of SDH and Local Extreme Value method （LEV） are studied and applied to simulate the actually measured radar data. The results show that the given discrimination is effective to reduce false alarms during dim targets detection.

Space-time clutter model for airborne bistatic radar with non-Gaussian statistics

To validate the potential space-time adaptive processing （STAP） algorithms for airborne bistatic radar clutter suppression under nonstationary and non-Gaussian clutter environments, a statistically non-Gaussian, space-time clutter model in varying bistatic geometrical scenarios is presented. The inclusive effects of the model contain the range dependency of bistatic clutter spectrum and clutter power variation in range-angle cells. To capture them, a new approach to coordinate system conversion is initiated into formulating bistatic geometrical model, and the bistatic non-Gaussian amplitude clutter representation method based on a compound model is introduced. The veracity of the geometrical model is validated by using the bistatic configuration parameters of multi-channel airborne radar measurement （MCARM） experiment. And simulation results manifest that the proposed model can accurately shape the space-time clutter spectrum tied up with specific airborne bistatic radar scenario and can characterize the heterogeneity of clutter amplitude distribution in practical clutter environments.

Clutter suppression for hypersonic vehicle-borne radar with frequency diverse array

The seriously range-ambiguous clutter is one of the main problems in clutter suppression for hypersonic vehicle-borne forward-looking radar. An approach based on the frequency diverse array (FDA) technique is proposed to mitigate the range ambiguous clutter. The frequency increment is designed to distinguish the clutter at ambiguous ranges and suppress the clutter by using a subspace projection algorithm. On the platform with high altitude or limited array antennas, the proposed method performs better for its independence of the elevation degrees-of-freedom (DOF). Finally, simulation results verify the effectiveness of the proposed method.

Modified GIT model for predicting wind-speed behavior of low-grazing-angle radar sea clutter

A modified GIT model for describing the variational trend of mean clutter reflectivity as a function of wind speed is proposed. It uses two slope adjustment factors and two critical wind-speed factors to define and adjust the increasing slope of reflectivity with respect to wind speed. In addition, it uses a constant factor to compensate the overall amplitude of clutter reflectivity. The performance of the modified GIT model has been verified on the basis of the L-band low-grazing-angle radar sea clutter data. The results are in good agreement with the experimental data, indicating that the model is more effective in predicting the wind-speed behavior of clutter reflectivity than the conventional GIT model, especially for lower and higher wind speeds. We believe that the proposed model can provide deeper insights into the relationship between radar sea clutter reflectivity and sea state conditions.

HF radar sea clutter rejection by nonlinear projections

In the background of signal detection for high frequency （I/F） radar, the sea clutter is quite significant and can mask some weak target signals. A new clutter rejection method named “nonlinear projection” is given to improve the SNR of the target. This approach is based on the recent observation that HF sea clutter may be modeled as a nonlinear deterministic dynamical system. After approximating the multidimensional reconstruction of the clutter by a low-dimensional attractor, projections onto this attractor can separate the clutter from other components. Real sea clutter, simulated target data and real target data are used to show that a nonlinear clutter rejection method is a promising technique to suppress sea clutter and enhances target detection.

Application of Fuzzy C-mean Cluster Algorithm on Clutter Tracking

This paper introduces a clutter tracking technique used forairborne PD radar. Combining the clutter feature of the airborne PDradar and characteristic of fuzzy C-means clustering algorithm, theauthors apply this algorithm to the clutter tracking, and present theflow chart. A method of defining the fuzzy membership function isalso proposed. The algorithm has been verified to be suc- cessful inseveral typical experiments.

Estimation of sea clutter inherent Doppler spectrum from shipborne S-band radar sea echo

Measurement of shipborne radar sea echo is instrumental in collecting the sea clutter data in open sea areas.However,the ship movement would introduce an extra Doppler component into the spectrum of the sea clutter,so the sea clutter inherent spectrum must be estimated prior to investigating the sea clutter Doppler characteristics from the shipborne radar sea echo.In this paper we show some results about a shipborne sea clutter measurement experiment that was conducted in the South China Sea in a period between 2017 and 2018;abundant clutter data have been collected by using a shipborne S-band clutter measurement radar.To obtain the sea clutter inherent Doppler spectrum from these data,an estimation method,based on the mapping relationship between the shipborne clutter spectrum and the inherent clutter spectrum,is proposed.This method is validated by shipborne clutter data sets under the same measuring conditions except for the ship speed.Using this method,the characteristics of the Doppler spectrum lineshapes in the South China Sea are calculated and analyzed according to different sea states,wave directions,and radar resolutions,which can be instrumental in designing the radar target detection algorithms.

Fractal-based weak target detection within sea clutter

The target on the sea surface is complex and difficult to detect due to the interference of backscattered returns from the sea surface illuminated by the radar pulse. Detrended fluctuation analysis （DFA） has been used successfully to extract the time-domain Hurst exponent of sea-clutter series. Since the frequency of the sea clutter mainly concentrates around Doppler center so that we consider to extract frequency-do- main fractal characterization and then detect a weak target within sea clutter by using the difference of frequency-domain fractal characterization. The generalized detrended fluctuation analysis （GDFA） is more flexible than traditional DFA owing to its smoothing action for the clutters. In this paper, we apply the GDFA to evaluate the generalized Hurst exponent of sea-clutter series in the frequency domain. The difference of generalized Hurst exponents between different sea-clutter range bins would be used to determine whether the target exists. Moreover, some simulations with the real IPIX radar data have also been demonstrated in order to suooort this conclusion.

A statistical distribution of quad-pol X-band sea clutter time series acquired at a grazing angle

Although the complex Wishart distribution has been widely used to analyze the statistic properties of quad-pol SAR spatial data, the applicability of this complex distribution to the time series of sea clutter is rarely discussed.The measured data of the quad-pol X-band marine radar demonstrate that the time series of the sea echoes are also satisfied the circular Gaussian distributions if the low intensity signals, which are mainly dominated by a radar noise, in the shadow regions of the large-scale waves are removed. On the basis of this fact, the probability density functions（PDFs） of the intensity as well as the phase, the real and the imaginary parts of the sea echoes obtained by the marine radar have been derived, and the theoretical models are all expressed in closed forms. In order to validate the theoretical results, the PDFs are compared with the experimental data collected by the Mc Master IPIX radar. And the comparisons show that the PDF models are in good agreement with the experimental data.

CLUTTER SUPPRESSION METHOD IN GPR USING PARTICLE CLUSTERING

In this paper, a novel clutter suppression method in Ground Penetrating Radar (GPR) is proposed. Time segments of hill are represented by their corresponding particle in B-scan. Those particles in B-scan are clustered to represent reflectors (such as buried targets, air-soil interface). The clusters of buried target have a particle sequence with single peak. Therefore, if the particles donot belong to the cluster of buried target, time segment they represent will be suppressed. Experimental results and simulation are provided to demonstrate that the new algorithm outperforms existing approaches.

Bayesian track-before-detect algorithm for nonstationary sea clutter

Radar detection of small targets in sea clutter is a particularly demanding task because of the nonstationary characteristic of sea clutter.The track-before-detect(TBD)filter is an effective way to increase the signal-to-clutter ratio(SCR),thus improving the detection performance of small targets in sea clutter.To cope with the nonstationary characteristic of sea clutter,an easily-implemented Bayesian TBD filter with adaptive detection threshold is proposed and a new parameter estimation method is devised which is integrated into the detection process.The detection threshold is set according to the parameter estimation result under the framework of information theory.For detection of closely spaced targets,those within the same range cell as the one under test are treated as contribution to sea clutter,and a successive elimination method is adopted to detect them.Simulation results prove the effectiveness of the proposed algorithm in detecting small targets in nonstationary sea clutter,especially closely spaced ones.

Optimal set integer programming algorithm for multiple maneuvering targets tracking in clutter

The aim of this paper is to solve the problems of multitarget tracking in clutter. Firstly, the data association of measurement-to-target is formulated as an integer programming problem. Through using the linear programming （LP） based branchand-bound method and adjusting the constraint conditions, an optimal set integer programming （OSIP） algorithm is then proposed for tracking multiple non-maneuvering targets in clutter. For the case of maneuvering targets, this paper introduces the OSIP algorithm into the filtering step of the interacting multiple model （IMM） algorithm resulting in the IMM based on OSIP algorithm. Extensive Monte Carlo simulations show that the presented algorithms can obtain superior estimations even in the case of high density noises.